Article(id=1241408881042191148, tenantId=1146029695717560320, journalId=1227999626482147330, issueId=1241408875602178849, articleNumber=null, orderNo=null, doi=10.16579/j.issn.1001.9669.2025.08.020, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1696780800000, receivedDateStr=2023-10-09, revisedDate=1701619200000, revisedDateStr=2023-12-04, acceptedDate=null, acceptedDateStr=null, onlineDate=1773904541501, onlineDateStr=2026-03-19, pubDate=1755187200000, pubDateStr=2025-08-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773904541501, onlineIssueDateStr=2026-03-19, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773904541501, creator=13701087609, updateTime=1773904541501, updator=13701087609, issue=Issue{id=1241408875602178849, tenantId=1146029695717560320, journalId=1227999626482147330, year='2025', volume='47', issue='8', pageStart='1', pageEnd='174', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773904540204, creator=13701087609, updateTime=1773904658798, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241409373071798309, tenantId=1146029695717560320, journalId=1227999626482147330, issueId=1241408875602178849, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241409373071798310, tenantId=1146029695717560320, journalId=1227999626482147330, issueId=1241408875602178849, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=168, endPage=174, ext={EN=ArticleExt(id=1241408881352569650, articleId=1241408881042191148, tenantId=1146029695717560320, journalId=1227999626482147330, language=EN, title=Optimization design of cam linkage mechanism for paper folding section of carton folding machine, columnId=1240594158461703059, journalTitle=Journal of Mechanical Strength, columnName=Optimization·Reliability, runingTitle=null, highlight=null, articleAbstract=

This article took the folding section cam linkage mechanism of a carton folding machine as an example.Firstly, a preliminary design of the cam was carried out based on actual working conditions. Then, combined with the analytical method designing the cam mechanism based on the allowable pressure angle of the cam, a mathematical model was established with the swing rod angle and the center distance between the cam and the swing rod as design variables. Using the NSGA-Ⅱ optimization algorithm, perform multi-objective optimization design on the cam linkage mechanism and select the optimal solution from the generated Pareto solution set. Based on the optimization results, the preliminary design of the cam linkage combination mechanism was adjusted, and the contour of the cam was obtained through Matlab programming,verifying that the optimized cam pressure angle met the allowable pressure angle. Finally, simulation analysis was conducted on the optimized cam linkage mechanism using Adams software. It is found that the displacement, velocity, and acceleration of the blade movement meet the design requirements, verifying the correctness and feasibility of the optimization results. At the same time, it also provides a reference method for the optimization design of other cam linkage mechanisms.

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DENG Yuanchao, E-mail:
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以纸盒折边机折纸段凸轮连杆机构为例,首先,根据实际工况对凸轮进行初步设计;然后,结合凸轮许用压力角设计凸轮机构的解析法,以摆杆转角和凸轮与摆杆间中心距为设计变量建立数学模型。利用NSGA-Ⅱ优化算法,对凸轮连杆机构进行多目标优化设计,并从生成的Pareto解集中选取最优解。根据优化结果对初步设计的凸轮连杆组合机构进行了调整,并采用Matlab软件编程获得凸轮的轮廓线,验证了优化后的凸轮压力角符合许用压力角。最后,利用Adams软件对优化后的凸轮连杆机构进行仿真分析。结果表明,铲刀运动的位移、速度和加速度符合设计要求,验证了优化结果的正确性和可行性,也为其他凸轮连杆机构的优化设计提供了可借鉴的方法。

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邓援超,男,1963年生,湖北孝感人,教授,硕士研究生导师;主要研究方向为机械设计理论及实用机械创新;E-mail:
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谢鼎越,男,1997年生,湖北襄阳人,硕士研究生;主要研究方向为机械设计及创新;E-mail:

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谢鼎越,男,1997年生,湖北襄阳人,硕士研究生;主要研究方向为机械设计及创新;E-mail:

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谢鼎越,男,1997年生,湖北襄阳人,硕士研究生;主要研究方向为机械设计及创新;E-mail:

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journalId=1227999626482147330, articleId=1241408881042191148, awardId=2020IM020800-01, language=CN, fundingSource=科技部创新方法专项(2020IM020800-01), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1241451344767276024, tenantId=1146029695717560320, journalId=1227999626482147330, articleId=1241408881042191148, xref=null, ext=[AuthorCompanyExt(id=1241451344775664633, tenantId=1146029695717560320, journalId=1227999626482147330, articleId=1241408881042191148, companyId=1241451344767276024, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=School of Mechanical Engineering, Hubei University of Technology, Wuhan 430068, China), AuthorCompanyExt(id=1241451344784053242, tenantId=1146029695717560320, journalId=1227999626482147330, articleId=1241408881042191148, companyId=1241451344767276024, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=湖北工业大学 机械工程学院,武汉 430068)])], figs=[ArticleFig(id=1241451348948996242, tenantId=1146029695717560320, journalId=1227999626482147330, articleId=1241408881042191148, language=EN, label=Fig.1, caption=Process of paper edge folding, figureFileSmall=3ZDCF8/bc6YhstuevhuASQ==, figureFileBig=M7venidIJ/wbbsY9/3hF7g==, tableContent=null), ArticleFig(id=1241451349053853847, tenantId=1146029695717560320, journalId=1227999626482147330, articleId=1241408881042191148, language=CN, label=图1, caption=面纸折边流程, figureFileSmall=3ZDCF8/bc6YhstuevhuASQ==, figureFileBig=M7venidIJ/wbbsY9/3hF7g==, tableContent=null), ArticleFig(id=1241451349188071581, tenantId=1146029695717560320, journalId=1227999626482147330, articleId=1241408881042191148, language=EN, label=Fig.2, caption=Origami section cam movement diagram

φ1-Push stage;φk-Distant rest segment;φ2-Return section;φh-Near rest segment.

, figureFileSmall=PYUx5tViJI38UTkNhpSThA==, figureFileBig=M5w1EfNRVeStbcsjkKi5XQ==, tableContent=null), ArticleFig(id=1241451349267763360, tenantId=1146029695717560320, journalId=1227999626482147330, articleId=1241408881042191148, language=CN, label=图2, caption=折纸段凸轮运动示意图

φ1-推程角;φk-远休止角;φ2-回程角;φh-近休止角。

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8 groups of Pareto optimal solutions

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指标
Index
基圆半径
Base circle radius r0/mm
O2AO2B长度比值
Length ratio of O2A to
O2Bl/L
摆杆O2B的长度
Length of O2B L/mm
第1组
Group 1
47.250 90.132 8170.617 2
第2组
Group 2
55.943 80.151 4147.856 8
第3组
Group 3
63.465 70.179 1173.793 6
第4组
Group 4
79.226 20.218 0156.226 3
第5组
Group 5
84.547 50.235 1162.697 5
第6组
Group 6
93.375 60.253 6149.481 9
第7组
Group 7
100.934 60.265 2136.318 1
第8组
Group 8
107.500 20.301 8169.417 5
), ArticleFig(id=1241451352497377508, tenantId=1146029695717560320, journalId=1227999626482147330, articleId=1241408881042191148, language=CN, label=表1, caption=

8组Pareto最优解

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指标
Index
基圆半径
Base circle radius r0/mm
O2AO2B长度比值
Length ratio of O2A to
O2Bl/L
摆杆O2B的长度
Length of O2B L/mm
第1组
Group 1
47.250 90.132 8170.617 2
第2组
Group 2
55.943 80.151 4147.856 8
第3组
Group 3
63.465 70.179 1173.793 6
第4组
Group 4
79.226 20.218 0156.226 3
第5组
Group 5
84.547 50.235 1162.697 5
第6组
Group 6
93.375 60.253 6149.481 9
第7组
Group 7
100.934 60.265 2136.318 1
第8组
Group 8
107.500 20.301 8169.417 5
), ArticleFig(id=1241451352593846506, tenantId=1146029695717560320, journalId=1227999626482147330, articleId=1241408881042191148, language=EN, label=Tab.2, caption=

Cam parameters

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参数
Parameter
基圆半径
Base circle radius r0/mm
摆杆最大转角
Maximum swing angle of the swing bar ψm/(°)
中心距
Center distance a/mm
O2A长度
Length of O2Al/mm
O2B长度
Length of O2BL/mm
值Value93.375 640.427 9117.832 637.908 6149.481 9
), ArticleFig(id=1241451352694509806, tenantId=1146029695717560320, journalId=1227999626482147330, articleId=1241408881042191148, language=CN, label=表2, caption=

凸轮参数

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参数
Parameter
基圆半径
Base circle radius r0/mm
摆杆最大转角
Maximum swing angle of the swing bar ψm/(°)
中心距
Center distance a/mm
O2A长度
Length of O2Al/mm
O2B长度
Length of O2BL/mm
值Value93.375 640.427 9117.832 637.908 6149.481 9
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纸盒折边机折纸段凸轮连杆机构的优化设计
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谢鼎越 , 邓援超 , 蔡宇飞 , 宋志成
机械强度 | 优化·可靠性 2025,47(8): 168-174
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机械强度 | 优化·可靠性 2025, 47(8): 168-174
纸盒折边机折纸段凸轮连杆机构的优化设计
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谢鼎越 , 邓援超 , 蔡宇飞, 宋志成
作者信息
  • 湖北工业大学 机械工程学院,武汉 430068
  • 谢鼎越,男,1997年生,湖北襄阳人,硕士研究生;主要研究方向为机械设计及创新;E-mail:

通讯作者:

邓援超,男,1963年生,湖北孝感人,教授,硕士研究生导师;主要研究方向为机械设计理论及实用机械创新;E-mail:
Optimization design of cam linkage mechanism for paper folding section of carton folding machine
Dingyue XIE , Yuanchao DENG , Yufei CAI, Zhicheng SONG
Affiliations
  • School of Mechanical Engineering, Hubei University of Technology, Wuhan 430068, China
出版时间: 2025-08-15 doi: 10.16579/j.issn.1001.9669.2025.08.020
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以纸盒折边机折纸段凸轮连杆机构为例,首先,根据实际工况对凸轮进行初步设计;然后,结合凸轮许用压力角设计凸轮机构的解析法,以摆杆转角和凸轮与摆杆间中心距为设计变量建立数学模型。利用NSGA-Ⅱ优化算法,对凸轮连杆机构进行多目标优化设计,并从生成的Pareto解集中选取最优解。根据优化结果对初步设计的凸轮连杆组合机构进行了调整,并采用Matlab软件编程获得凸轮的轮廓线,验证了优化后的凸轮压力角符合许用压力角。最后,利用Adams软件对优化后的凸轮连杆机构进行仿真分析。结果表明,铲刀运动的位移、速度和加速度符合设计要求,验证了优化结果的正确性和可行性,也为其他凸轮连杆机构的优化设计提供了可借鉴的方法。

凸轮连杆机构  /  许用压力角  /  NSGA-Ⅱ优化算法  /  多目标优化  /  仿真分析

This article took the folding section cam linkage mechanism of a carton folding machine as an example.Firstly, a preliminary design of the cam was carried out based on actual working conditions. Then, combined with the analytical method designing the cam mechanism based on the allowable pressure angle of the cam, a mathematical model was established with the swing rod angle and the center distance between the cam and the swing rod as design variables. Using the NSGA-Ⅱ optimization algorithm, perform multi-objective optimization design on the cam linkage mechanism and select the optimal solution from the generated Pareto solution set. Based on the optimization results, the preliminary design of the cam linkage combination mechanism was adjusted, and the contour of the cam was obtained through Matlab programming,verifying that the optimized cam pressure angle met the allowable pressure angle. Finally, simulation analysis was conducted on the optimized cam linkage mechanism using Adams software. It is found that the displacement, velocity, and acceleration of the blade movement meet the design requirements, verifying the correctness and feasibility of the optimization results. At the same time, it also provides a reference method for the optimization design of other cam linkage mechanisms.

Cam linkage mechanism  /  Allowable pressure angle  /  NSGA-Ⅱ optimization algorithm  /  Multi objective optimization  /  Simulation analysis
谢鼎越, 邓援超, 蔡宇飞, 宋志成. 纸盒折边机折纸段凸轮连杆机构的优化设计. 机械强度, 2025 , 47 (8) : 168 -174 . DOI: 10.16579/j.issn.1001.9669.2025.08.020
Dingyue XIE, Yuanchao DENG, Yufei CAI, Zhicheng SONG. Optimization design of cam linkage mechanism for paper folding section of carton folding machine[J]. Journal of Mechanical Strength, 2025 , 47 (8) : 168 -174 . DOI: 10.16579/j.issn.1001.9669.2025.08.020
在凸轮连杆组合机构的设计中,为使机构以最佳状态运行,需要对各部分的尺寸和相对位置进行优化设计。目前常采用优化算法进行机构设计,周红妮等[1]采用多目标遗传算法(NSGA-Ⅱ)实现了汽车前桥转向机构的多目标优化。李秀兰等[2]采用修正的遗传算法对目标函数进行了全局搜索,获得了最佳的凸轮轮廓和连杆长度。顾寄南等[3]以曲柄齿轮齿条的齿轮摆角、齿轮角加速度以及齿轮齿条重合对为优化目标,运用NSGA-Ⅱ算法对设计参数进行了多目标优化,并从解集中确定了最优设计方案。
为获得设计合理、结构紧凑的摆动从动件凸轮机构,华大年[4]基于类速度图提出了根据许用压力角设计最小尺寸摆动从动件平面凸轮的解析法。常勇等[5-6]对他提出的解析法进行了注记和补充,提出了华大年方法的适用范围和不适用情况的产生原理。
在一款高档纸盒的生产中,需要将过胶后的纸盒面纸的包边侧翻折180°,并精确贴合到内侧的灰纸板上[7],针对该需求设计的纸盒折边机采用凸轮连杆组合机构,使用2个凸轮推动连杆机构实现预定的工艺动作。本文针对纸盒折边机的折纸段凸轮连杆机构进行设计,该机构采用凸轮摆杆与平面连杆组合从而实现预定的动作。在已知推杆运动规律和凸轮许用压力角的条件下,结合凸轮许用压力角设计最小尺寸的凸轮摆杆机构,并根据NSGA-Ⅱ优化算法对摆杆转角、凸轮与摆杆中心距等参数进行多目标优化设计,从而获取最优的结构设计方案,最终通过编制程序验证设计的正确性。
图1(a)所示为围条未折边时的状态,即围条底部和面纸初步贴合的状态;图1(b)所示为由上料机械手将未折边围条放到工位上进行预折边的围条;图1(c)所示为面纸包边贴合到围条后的状态。
折纸段凸轮动作过程可分为推程段、远休止段、回程段和近休止段4个部分,即将铲刀由M点推到N点并返回,如图2所示(虚线表示连杆机构部分最终位置),其中O2点位于X轴上,BB'点在同一竖直线上,其坐标分别为B(130.12 mm,-51.65 mm)、B'(130.12 mm,51.65 mm),O2AO2B共线。其中未知的量有:O1点、O2点的位置,摆杆O2B的长度以及O2点到滚子A的距离。
1)推程段。凸轮转动从而推动滚子A带动摆杆O2BO2点转动,通过各个连杆推动铲刀移动,当B点转动到B'点时,铲刀向前移动并完成面纸折边动作,即从M点推动到N点,推程角φ1=π/3。
2)远休止段。凸轮使摆杆O2B保持在O2B'位置,此时铲刀静止保压,以及等待其他工艺动作完成,远休止角
3)回程段。铲刀完成送纸动作后,凸轮进入回程,通过回程段廓线使滚子A平稳过渡到基圆上,将铲刀从N点推回到M点,回程角φ2=π/6。
4)近休止段。摆杆O2B回到初始位置,近休止角φh=π/6。
铲刀在折纸过程中要尽可能无冲击且速度变化平稳,以避免折边的面纸出现褶皱现象,因此从动件运动规律采用正弦加速度运动规律。根据纸盒折边机中组合机构的动作要求,凸轮采用槽道凸轮机构,故凸轮往返行程皆为推程。摆杆O2B的运动规律表达式为
式中,ψ为摆角;v为角速度;a0为角加速度;φ为凸轮转角,φ∈[0,ϕ],其中,ϕ为最大推程角;ψmax为摆杆O2B的最大摆角。
以摆动从动件的运动规律设计平面凸轮的轮廓线时,必须确定凸轮的基圆半径、摆杆长度和两者的中心距。在折纸段凸轮机构的设计实例中,凸轮和摆杆的中心距可根据机构总体尺寸确定大致范围,但凸轮基圆直径和摆杆长度未知。
为获得整体轻便紧凑且受力较好的凸轮机构,需要凸轮的基圆尺寸尽可能小,基圆尺寸又与压力角有直接关联,而这两者又是矛盾的。为解决这一问题,按许用压力角设计凸轮最小尺寸便成了最优选择。
图3所示,在直角坐标系O2XY中,原点O2为摆杆轴心,X轴沿摆杆初始位置O2A0,由X轴以O2点为轴心沿逆时针旋方向转90°得到Y轴,O2Am为摆杆终止位置,ψm为摆杆动程角。
图3所示,当摆杆推程与凸轮转向相同时,设摆杆在某位置O2A,在上面取AH='(其中,l为摆杆O2A的长度;ψ'为摆杆类角速度,),过H点作与HA夹角为γ(许用传动角)的直线h-h,其方程为
式中,lγ均为常数;ψψ'均为关于凸轮转角φ的函数。因此,式(2)可写为F(XYφ)=0的形式,为关于变量φ的直线族。当凸轮转角φ变化时,直线族将会形成一条包络曲线,包络线的坐标可根据微分几何求解,即
将式(3)联立求解,即可得包络曲界线Ⅰ为
式中,N为符号变量,且当摆杆推程与凸轮转向相同时,N=1。
图3所示,当摆杆推程与凸轮转向相反时,设摆杆在某位置O2A,在上面取AH'=',过H'点作与H'A夹角为γ的直线h'- h',其方程为
式中,N=-1。
此时,按照由式(2)推导出式(4)的方法可推导出曲界线Ⅳ的方程。因此,式(4)为两曲界线(Ⅰ,Ⅳ)的通用表达式,且当摆杆推程与凸轮转向相反时,N=-1。
在槽道凸轮机构中,摆杆往返皆为推程,根据文献[8]的研究,凸轮轴心应位于2个曲界线Ⅰ和Ⅳ所围成的阴影区域内,其最小基圆半径位于2个曲界线的交点,如图3(b)所示。由于该交点在摆杆往返时对应的摆角一般不重合,所以在应用式(4)时,推程段设N=1,ψ=ψ1;回程段设N=-1,ψ=ψ2。由此可得
式中,ψ1ψ2对应的角位移分别为φ1φ2。将式(6)、式(7)联立消去XY
式(8)为含有φ1φ2 这2个变量的非线性方程组,可采用牛顿法进行求解,并将求解后的结果代入式(6)或(7)得到XY,可得出计算式[9]
XY代入式(9)、式(10),根据选取的实际中心距a,代入式(11)、式(12)可解出凸轮基圆半径r0和摆杆O2A长度l
在工程实际中,常遇到需要在给定范围内寻找多个目标均为最佳情况的优化问题,而多个数值目标在给定区域内的最优问题称为多目标优化问题[10]。NSGA-Ⅱ算法是当前应用最广泛的遗传算法之一,具有速度快,解集收敛性较好的特点。由于多目标优化问题中的多个子目标是相互冲突的,所以NSGA-Ⅱ算法得出的解不是唯一解,而是一组最优解集合,称为Pareto解集[11]。当获得Pareto解集后,根据工程实际经验选出一组比较满意的解。
凸轮机构的尺寸大小往往取决于凸轮的大小,为使机构更加紧凑,应尽量减小凸轮的基圆半径[12]145-148。因此定义凸轮的基圆半径作为第1优化目标,即
摆杆O2B是由滚子A推动而转动的,O2AO2B长度的比值越小,机构的传力比越大,其摩擦产生损耗也就越大,凸轮轴受到的压力也越大。因此,定义O2AO2B长度lL的比值为第2优化目标,即
由于采用的算法是以目标函数分量取极小值为目标,所以对lL的比值取负值以进行优化。
优化变量的选取要能影响优化目标且可以独立控制[12]145-148。如图2所示,根据已知参数,B点和B'点之间距离H0=103.3 mm,X轴为BB'的垂直平分线,设摆杆从O2BO2B'的转角为ψm,则摆杆O2B长度L
式中,ψm为摆杆O2B的最大转角;a为凸轮轴心O1和摆杆轴心O2之间的中心距。
摆杆O2B长度直接影响第2优化目标O2AO2B(长度分别为lL)的比值的取值,且由式(15)可知,H0一定时,影响摆杆O2B长度L的参数就只有摆杆O2B的最大转角ψm。此外,凸轮轴心O1和摆杆轴心O2之间的中心距a决定了第1优化目标基圆半径的取值。
因此,设定摆杆O2B的最大转角ψm和凸轮轴心O1和摆杆轴心O2之间的中心距a为设计变量,即
考虑到纸盒折边机机构整体的结构大小,限制实际中心距a的范围为
由于摆杆转角ψm关系到摆杆O2B长度,太小会增大机构尺寸,太大会增大最大压力角且使各部件之间的比例相差过大。因此,结合本实例,为确保机构尺寸合理,定义摆杆转角ψm的范围为
根据所推导出的各个变量之间的相互关系,采用Matlab软件进行编程。设定优化算法种群数为50,迭代次数为100,运行后得到Pareto最优解解集,如图4所示,*号表示NSGA-Ⅱ算法得出的最优解分布。
图4可以看出,左上角的解中,O2AO2B长度比值较大,凸轮推动摆杆的力较小,但此时的基圆半径较大,整体结构尺寸较大;而右下角的解则相反,O2AO2B长度比值较小,将会导致机构在运动时凸轮所受到的力较大,机构的力学性能较差。因此,从Pareto最优解集中选取中间区域的8组方案(表1),在图4红色圈内,并利用多目标加权灰靶决策模型做决策,进而选取出一组最优的设计方案[13]。决策过程如下:
1)8组解集对应的矩阵R
在优化目标中,O2AO2B长度的比值影响着机构的力学性能,对机构运动状态有主要影响,故取较大权重;基圆半径和摆杆O2B的长度L影响着机构的整体尺寸,对机构运动有一般影响,取较小权重,因此将权重设定为
式中,e1、e2、e3分别对应基圆半径和O2AO2B长度的比值与摆杆O2B的长度L的权重。
2)决策矩阵。工程项目的决策中,由于不同的指标有不同的量纲,在决策中无法直接进行比较,所以需要将决策矩阵进行标准化。[-1,1]区间决策算子可以对高于平均水平的决策赋0~1的正值,对低于平均水平的赋-1~0的负值,从而保证对于决策有奖有罚。本次主要针对的指标均为效益型指标,故采用表达式为
越大越好时,为
越小越好时,为
由式(21)~式(23)得出决策矩阵K,为
3)结合优化目标,求最佳结果向量,即
4)计算各个方案向量与最佳结果向量的距离:
其结果分别为δ1=1.524 4,δ2=1.169 2,δ3=1.337 9,δ4=0.970 3,δ5=1.045 7,δ6=0.932 3,δ7=0.964 8,δ8=1.326 0,可以看出δ6最小,表示其距离最佳结果的距离最近。因此,选用第6组作为最优解决方案,即基圆半径r0=93.375 6 mm,O2AO2B长度比值l/L=0.253 6。此时对应的凸轮参数如表2所示。
根据式(1)中摆杆的运动规律和表2中摆杆转角及凸轮基圆半径,采用Matlab软件绘制程序绘制凸轮理论轮廓线、实际轮廓线、基圆[14],如图5所示。
编制凸轮压力角程序,获取凸轮的压力角曲线,如图6所示。
图6可知,凸轮的最大压力角为40°,符合设定的许用压力角[α],满足设计要求。
基于前文的计算,可以确定凸轮连杆机构中各个杆以及凸轮的各项参数。为了更直观地验证所设计的凸轮连杆机构的运动参数是否符合设计要求,在Adams软件中建立凸轮连杆机构的运动模型,并对其进行仿真,得到了铲刀运动的位移、速度和加速度曲线,如图7~图9所示。
图7可知,铲刀从起始位置(2.35 mm)运动到最远位置(45.86 mm),总位移为43.51 mm,满足铲刀位移需在40~50 mm的要求。并且在15~35 s间铲刀的位移没有太大的变化,可以满足在折边后对纸板进行保压的要求,使面纸与灰纸板贴合紧密。
图8可知,铲刀的运动速度最高达到46.55 mm/s,满足设计需求。虽然在33~36 s段速度存在突变,但此处属于凸轮的回程段,并且在第5节中已经验证回程段的凸轮压力角满足设计要求,故此处突变合理,不影响机构整体的运行和功能的实现。
图9可知,铲刀的运动加速度在33~36 s产生突变并且达到峰值149.37 mm/s2,与图8中的情况类似,此阶段属于凸轮回程段,且此加速度由于数值较小,所产生的力和冲击不大,故不会影响机构的整体运行和功能的实现。
以纸盒折边机折纸段凸轮连杆机构为例,对机构进行优化,得出以下主要结论:
1)根据凸轮许用压力角设计凸轮,并用NSGA-Ⅱ多目标算法对凸轮进行优化设计,随后用Matlab软件验证了优化后的凸轮压力角符合设计要求,证明了该方法的有效性。
2)利用Adsms软件对优化后的凸轮连杆机构进行仿真分析,验证了该凸轮连杆机构的运动的可靠性和可行性,为其他凸轮连杆组合机构的优化设计提供了可借鉴的方法。
所提的方法还可以通过改变凸轮推程角、远休止角、回程角与近休止角和采用不同的组合机构进一步优化凸轮连杆机构的运动速度和加速度,以降低其速度和加速度的峰值。限于篇幅,这些研究暂时还未开展,这也是后续需要进行研究的内容。在仿真得到的铲刀运动加速度图中,近休止段加速度有所变化,此变化的原因也需要进一步思考。
  • 科技部创新方法专项(2020IM020800-01)
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2025年第47卷第8期
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doi: 10.16579/j.issn.1001.9669.2025.08.020
  • 接收时间:2023-10-09
  • 首发时间:2026-03-19
  • 出版时间:2025-08-15
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  • 收稿日期:2023-10-09
  • 修回日期:2023-12-04
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Innovation Methods Special Project of the Ministry of Science and Technology(2020IM020800-01)
科技部创新方法专项(2020IM020800-01)
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    湖北工业大学 机械工程学院,武汉 430068

通讯作者:

邓援超,男,1963年生,湖北孝感人,教授,硕士研究生导师;主要研究方向为机械设计理论及实用机械创新;E-mail:
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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